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Invigorated Chameleon Swarm Optimization-Based Ad-Hoc On-Demand Distance Vector (ICSO-AODV) for Minimizing Energy Consumption in Healthcare Mobile Wireless Sensor Networks


Affiliations
1 Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India
 

This study explores the advancements in Wireless Sensor Networks (WSNs) and their application in Mobile Wireless Sensor Networks (MWSNs), particularly within Healthcare Mobile Wireless Sensor Networks (H-MWSNs). Routing in WSNs poses challenges, including adaptability to dynamic environments and efficient path computation. Addressing these challenges, this research propose the Floyd-Warshall-based Ad-hoc On-Demand Distance Vector (FW-AODV) approach. FW-AODV seamlessly integrates the Floyd-Warshall Algorithm with the AODV protocol, providing optimal path computation and dynamic routing capabilities. This integration is particularly promising for MWSNs, where adaptability and efficiency are crucial, especially in healthcare applications. We elucidate the working mechanism of FW-AODV, detailing its iterative rejuvenation process and dynamic color-based communication. Through simulations, this research evaluate FW-AODV's performance in dynamic and challenging WSN environments. Our results demonstrate FW-AODV's effectiveness in enhancing routing efficacy, resilience, and adaptability, offering a robust solution for modern healthcare-focused WSNs.

Keywords

FW-AODV, Optimal Path, Dynamic Routing, Chameleon Optimization, MWSN, Healthcare MWSN, Routing.
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  • Invigorated Chameleon Swarm Optimization-Based Ad-Hoc On-Demand Distance Vector (ICSO-AODV) for Minimizing Energy Consumption in Healthcare Mobile Wireless Sensor Networks

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Authors

S. Kawsalya
Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India
D. Vimal Kumar
Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India
D. Vimal Kumar
Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, India

Abstract


This study explores the advancements in Wireless Sensor Networks (WSNs) and their application in Mobile Wireless Sensor Networks (MWSNs), particularly within Healthcare Mobile Wireless Sensor Networks (H-MWSNs). Routing in WSNs poses challenges, including adaptability to dynamic environments and efficient path computation. Addressing these challenges, this research propose the Floyd-Warshall-based Ad-hoc On-Demand Distance Vector (FW-AODV) approach. FW-AODV seamlessly integrates the Floyd-Warshall Algorithm with the AODV protocol, providing optimal path computation and dynamic routing capabilities. This integration is particularly promising for MWSNs, where adaptability and efficiency are crucial, especially in healthcare applications. We elucidate the working mechanism of FW-AODV, detailing its iterative rejuvenation process and dynamic color-based communication. Through simulations, this research evaluate FW-AODV's performance in dynamic and challenging WSN environments. Our results demonstrate FW-AODV's effectiveness in enhancing routing efficacy, resilience, and adaptability, offering a robust solution for modern healthcare-focused WSNs.

Keywords


FW-AODV, Optimal Path, Dynamic Routing, Chameleon Optimization, MWSN, Healthcare MWSN, Routing.

References





DOI: https://doi.org/10.22247/ijcna%2F2024%2F224446